The purpose of these studies is to develop and evaluate a practical screening method for nodular disease using dual-energy chest radiography. The dual-energy technique is used to subtract either bone or soft-tissue structures from a radiographic image, by utilizing the different energy dependence of X-ray attenuation in bone and soft-tissue. The technique uses images acquired at two different X-ray energies to solve for the bone and soft-tissue components. The diagnostic advantages of dual-energy are that the visibility of soft-tissue nodules is improved by eliminating the presence of overlying ribs, and the calcium content of nodules may be determined by viewing the bone image. The dual-energy images are acquired simultaneously with a conventional radiograph, with little or no increase in patient dose, thereby making possible a clinically practical screening procedure. The resulting dual-energy images may be reviewed manually by a radiologist, and possibly in the future may be processed by automated nodule detection schemes to identify for further review those patients with potential nodules. The projects in this competing continuation application refine the dual- energy screening techniques developed in years 1-3 of the present grant. The specific studies in this proposal include: refinement of a new scatter-correction algorithm, refinement of noise-reduction algorithms, evaluation of new asymmetric screen-film cassettes for acquiring the complementary conventional image, evaluation of a new two-plate computed radiography approach for producing the complementary conventional image, detailed evaluation of image quality in dual-energy images, clinical evaluation of nodule detection using the hybrid conventional/dual-energy configuration, and evaluation of nodule detection using artificial neural networks to determine if dual-energy imaging provides improved specificity for computer-aided detection. In each of these areas of research, emphasis will be placed on detailed evaluation of technical improvement, practicality of implementation, and clinically-related diagnostic improvement.